A bibliometric analysis of earth science decision making for climate resilience: Linking data-driven models with SDG 13 and SDG 15

Decision-making in earth science is essential in addressing global sustainability problems where empirical data and sophisticated modeling need to be combined with human judgment. A bibliometric analysis of Scopus data from 2019 to 2025 uncovers patterns impacting the research enterprise surrounding earth science decision-making, with special reference given to land conservation, land use and sustainability, climate hazards, climate impacts, and climate mitigation. Significant growth in research productivity Overall, the results reflect a dramatic surge in research output with 2022 obviously standing in US, China and UK appear to be major contributors at the global level. Recent developments in investigation indicate that big data, machine learning, and artificial intelligence can be effectively employed to help decision makers improve environmental decisions with science-based methods. SDG15 is interestingly the second most important SDGs target among all after SDG13. Nonetheless, over and beyond digitalization and artificial intelligence, the embedding of energy research in a broader sustainable development framework is still lacking. The results underscore the role of integrating technology with cognitive-and social-based decision-making in increasing access to, and responsiveness of, sustainability management. Therefore, future research agenda should explicitly include SDG 7 under the umbrella framework as an indispensable complementary framework.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-03-04
DOI
https://doi.org/10.1051/e3sconf/202669601007/pdf
Primary Topic
Innovation, Sustainability, Human-Machine Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A bibliometric analysis of earth science decision making for climate resilience: Linking data-driven models with SDG 13 and SDG 15

Hasan Nuurul Hidaayatullaah, Linh Nguyễn Quang, Putri Lintang Utami, Eko Hariyono et al.
Springer Link (Chiba Institute of Technology)
Innovation, Sustainability, Human-Machine Systems
article

A bibliometric analysis of earth science decision making for climate resilience: Linking data-driven models with SDG 13 and SDG 15

Hasan Nuurul Hidaayatullaah, Linh Nguyễn Quang, Putri Lintang Utami, Eko Hariyono, Nadi Suprapto
article en

Abstract

Decision-making in earth science is essential in addressing global sustainability problems where empirical data and sophisticated modeling need to be combined with human judgment. A bibliometric analysis of Scopus data from 2019 to 2025 uncovers patterns impacting the research enterprise surrounding earth science decision-making, with special reference given to land conservation, land use and sustainability, climate hazards, climate impacts, and climate mitigation. Significant growth in research productivity Overall, the results reflect a dramatic surge in research output with 2022 obviously standing in US, China and UK appear to be major contributors at the global level. Recent developments in investigation indicate that big data, machine learning, and artificial intelligence can be effectively employed to help decision makers improve environmental decisions with science-based methods. SDG15 is interestingly the second most important SDGs target among all after SDG13. Nonetheless, over and beyond digitalization and artificial intelligence, the embedding of energy research in a broader sustainable development framework is still lacking. The results underscore the role of integrating technology with cognitive-and social-based decision-making in increasing access to, and responsiveness of, sustainability management. Therefore, future research agenda should explicitly include SDG 7 under the umbrella framework as an indispensable complementary framework.

Springer Link (Chiba Institute of Technology)
Ministrstvo za visoko šolstvo, znanost in tehnologijo, Lembaga Pengelola Dana Pendidikan
Openalex Percentile: Top 42%
Innovation, Sustainability, Human-Machine Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A bibliometric analysis of earth science decision making for climate resilience: Linking data-driven models with SDG 13 and SDG 15 — Hasan Nuurul Hidaayatullaah, Linh Nguyễn Quang, et al. · Springer Link (Chiba Institute of Technology) (2026) | TGRS Research Map | TGRS